Using String Comparison in Context for Improved Relevance Feedback in Different Text Media
Identifieur interne : 000256 ( Istex/Corpus ); précédent : 000255; suivant : 000257Using String Comparison in Context for Improved Relevance Feedback in Different Text Media
Auteurs : M. Lam-Adesina ; F. JonesSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2006.
Abstract
Abstract: Query expansion is a long standing relevance feedback technique for improving the effectiveness of information retrieval systems. Previous investigations have shown it to be generally effective for electronic text, to give proportionally better improvement for automatic transcriptions of spoken documents, and to be at best of questionable utility for optical character recognized scanned text documents. We introduce two corpus-based methods based on using a string-edit distance measure in context to automatically detect and correct transcription errors. One method operates at query-time and requires no modification of the document index file, and the other at index-time and operates using the standard query-time expansion process. Experimental investigations show these methods to produce improvements in relevance feedback for all three media types, but most significantly mean that relevance feedback can now successfully be applied to scanned text documents.
Url:
DOI: 10.1007/11880561_19
Links to Exploration step
ISTEX:66E6AA650E9D11341DE243DD7773075E3392078BLe document en format XML
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Previous investigations have shown it to be generally effective for electronic text, to give proportionally better improvement for automatic transcriptions of spoken documents, and to be at best of questionable utility for optical character recognized scanned text documents. We introduce two corpus-based methods based on using a string-edit distance measure in context to automatically detect and correct transcription errors. One method operates at query-time and requires no modification of the document index file, and the other at index-time and operates using the standard query-time expansion process. Experimental investigations show these methods to produce improvements in relevance feedback for all three media types, but most significantly mean that relevance feedback can now successfully be applied to scanned text documents.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Adenike M. 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Previous investigations have shown it to be generally effective for electronic text, to give proportionally better improvement for automatic transcriptions of spoken documents, and to be at best of questionable utility for optical character recognized scanned text documents. We introduce two corpus-based methods based on using a string-edit distance measure in context to automatically detect and correct transcription errors. One method operates at query-time and requires no modification of the document index file, and the other at index-time and operates using the standard query-time expansion process. Experimental investigations show these methods to produce improvements in relevance feedback for all three media types, but most significantly mean that relevance feedback can now successfully be applied to scanned text documents.</p></abstract><textClass><keywords scheme="Book Subject Collection"><list><label>SUCO11645</label><item><term>Computer Science</term></item></list></keywords></textClass><textClass><keywords scheme="Book Subject Group"><list><label>I</label><label>I18032</label><label>I21017</label><label>I18024</label><label>I15017</label><label>I15041</label><label>I16021</label><item><term>Computer Science</term></item><item><term>Information Storage and Retrieval</term></item><item><term>Artificial Intelligence (incl. 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Robotics)</BookSubject><BookSubject Code="I18024" Priority="3" Type="Secondary">Database Management</BookSubject><BookSubject Code="I15017" Priority="4" Type="Secondary">Data Structures</BookSubject><BookSubject Code="I15041" Priority="5" Type="Secondary">Coding and Information Theory</BookSubject><BookSubject Code="I16021" Priority="6" Type="Secondary">Algorithm Analysis and Problem Complexity</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup><BookContext><SeriesID>558</SeriesID></BookContext></BookInfo><BookHeader><EditorGroup><Editor AffiliationIDS="Aff16"><EditorName DisplayOrder="Western"><GivenName>Fabio</GivenName><FamilyName>Crestani</FamilyName></EditorName><Contact><Email>f.crestani@cis.strath.ac.uk</Email></Contact></Editor><Editor AffiliationIDS="Aff17"><EditorName DisplayOrder="Western"><GivenName>Paolo</GivenName><FamilyName>Ferragina</FamilyName></EditorName><Contact><Email>ferragina@di.unipi.it</Email></Contact></Editor><Editor AffiliationIDS="Aff18"><EditorName DisplayOrder="Western"><GivenName>Mark</GivenName><FamilyName>Sanderson</FamilyName></EditorName><Contact><Email>m.sanderson@sheffield.ac.uk</Email></Contact></Editor><Affiliation ID="Aff16"><OrgDivision>Department of Computer and Information Science</OrgDivision><OrgName>University of Strathclyde</OrgName><OrgAddress><Country>Scotland</Country></OrgAddress></Affiliation><Affiliation ID="Aff17"><OrgDivision>Dipartimento di Informatica</OrgDivision><OrgName>University of Pisa</OrgName><OrgAddress><Street>Largo B. Pontecorvo 3</Street><Postcode>56127</Postcode><City>Pisa</City><Country>Italy</Country></OrgAddress></Affiliation><Affiliation ID="Aff18"><OrgDivision>Department of Information Studies</OrgDivision><OrgName>University of Sheffield</OrgName><OrgAddress><City>Sheffield</City><Country>UK</Country></OrgAddress></Affiliation></EditorGroup></BookHeader><Part ID="Part7"><PartInfo TocLevels="0"><PartID>7</PartID><PartSequenceNumber>7</PartSequenceNumber><PartTitle>Information Retrieval Applications</PartTitle><PartChapterCount>4</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookTitle>String Processing and Information Retrieval</BookTitle></PartContext></PartInfo><Chapter ID="Chap19" Language="En"><ChapterInfo ChapterType="OriginalPaper" ContainsESM="No" NumberingDepth="2" NumberingStyle="ContentOnly" TocLevels="0"><ChapterID>19</ChapterID><ChapterDOI>10.1007/11880561_19</ChapterDOI><ChapterSequenceNumber>19</ChapterSequenceNumber><ChapterTitle Language="En">Using String Comparison in Context for Improved Relevance Feedback in Different Text Media</ChapterTitle><ChapterFirstPage>229</ChapterFirstPage><ChapterLastPage>241</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2006</CopyrightYear></ChapterCopyright><ChapterGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ChapterGrants><ChapterContext><SeriesID>558</SeriesID><PartID>7</PartID><BookID>978-3-540-45775-6</BookID><BookTitle>String Processing and Information Retrieval</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff19"><AuthorName DisplayOrder="Western"><GivenName>Adenike</GivenName><GivenName>M.</GivenName><FamilyName>Lam-Adesina</FamilyName></AuthorName><Contact><Email>adenike@computing.dcu.ie</Email></Contact></Author><Author AffiliationIDS="Aff19"><AuthorName DisplayOrder="Western"><GivenName>Gareth</GivenName><GivenName>J.</GivenName><GivenName>F.</GivenName><FamilyName>Jones</FamilyName></AuthorName><Contact><Email>gjones@computing.dcu.ie</Email></Contact></Author><Affiliation ID="Aff19"><OrgDivision>Centre for Digital Video Processing & School of Computing</OrgDivision><OrgName>Dublin City University</OrgName><OrgAddress><City>Dublin 9</City><Country>Ireland</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>Query expansion is a long standing relevance feedback technique for improving the effectiveness of information retrieval systems. Previous investigations have shown it to be generally effective for electronic text, to give proportionally better improvement for automatic transcriptions of spoken documents, and to be at best of questionable utility for optical character recognized scanned text documents. We introduce two corpus-based methods based on using a string-edit distance measure in context to automatically detect and correct transcription errors. One method operates at query-time and requires no modification of the document index file, and the other at index-time and operates using the standard query-time expansion process. Experimental investigations show these methods to produce improvements in relevance feedback for all three media types, but most significantly mean that relevance feedback can now successfully be applied to scanned text documents.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Using String Comparison in Context for Improved Relevance Feedback in Different Text Media</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Using String Comparison in Context for Improved Relevance Feedback in Different Text Media</title></titleInfo><name type="personal"><namePart type="given">Adenike</namePart><namePart type="given">M.</namePart><namePart type="family">Lam-Adesina</namePart><affiliation>Centre for Digital Video Processing & School of Computing, Dublin City University, Dublin 9, Ireland</affiliation><affiliation>E-mail: adenike@computing.dcu.ie</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Gareth</namePart><namePart type="given">J.</namePart><namePart type="given">F.</namePart><namePart type="family">Jones</namePart><affiliation>Centre for Digital Video Processing & School of Computing, Dublin City University, Dublin 9, Ireland</affiliation><affiliation>E-mail: gjones@computing.dcu.ie</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference [eBooks]" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2006</dateIssued><copyrightDate encoding="w3cdtf">2006</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: Query expansion is a long standing relevance feedback technique for improving the effectiveness of information retrieval systems. Previous investigations have shown it to be generally effective for electronic text, to give proportionally better improvement for automatic transcriptions of spoken documents, and to be at best of questionable utility for optical character recognized scanned text documents. We introduce two corpus-based methods based on using a string-edit distance measure in context to automatically detect and correct transcription errors. One method operates at query-time and requires no modification of the document index file, and the other at index-time and operates using the standard query-time expansion process. Experimental investigations show these methods to produce improvements in relevance feedback for all three media types, but most significantly mean that relevance feedback can now successfully be applied to scanned text documents.</abstract><relatedItem type="host"><titleInfo><title>String Processing and Information Retrieval</title><subTitle>13th International Conference, SPIRE 2006, Glasgow, UK, October 11-13, 2006. Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Fabio</namePart><namePart type="family">Crestani</namePart><affiliation>Department of Computer and Information Science, University of Strathclyde, Scotland</affiliation><affiliation>E-mail: f.crestani@cis.strath.ac.uk</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Paolo</namePart><namePart type="family">Ferragina</namePart><affiliation>Dipartimento di Informatica, University of Pisa, Largo B. Pontecorvo 3, 56127, Pisa, Italy</affiliation><affiliation>E-mail: ferragina@di.unipi.it</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Mark</namePart><namePart type="family">Sanderson</namePart><affiliation>Department of Information Studies, University of Sheffield, Sheffield, UK</affiliation><affiliation>E-mail: m.sanderson@sheffield.ac.uk</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="Book Series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2006</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book Subject Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book Subject Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I18032">Information Storage and Retrieval</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. Robotics)</topic><topic authority="SpringerSubjectCodes" authorityURI="I18024">Database Management</topic><topic authority="SpringerSubjectCodes" authorityURI="I15017">Data Structures</topic><topic authority="SpringerSubjectCodes" authorityURI="I15041">Coding and Information Theory</topic><topic authority="SpringerSubjectCodes" authorityURI="I16021">Algorithm Analysis and Problem Complexity</topic></subject><identifier type="DOI">10.1007/11880561</identifier><identifier type="ISBN">978-3-540-45774-9</identifier><identifier type="eISBN">978-3-540-45775-6</identifier><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="BookTitleID">141649</identifier><identifier type="BookID">978-3-540-45775-6</identifier><identifier type="BookChapterCount">31</identifier><identifier type="BookVolumeNumber">4209</identifier><identifier type="BookSequenceNumber">4209</identifier><identifier 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